Exploring daily wind data using the Meteostat Python Library
Group Members: Travis, Ira, Micah
Course: Data Science – Phase 2
Goal: Explore and compare wind trends in distinct U.S. regions
Source: Meteostat Python API
Dataset Type: Aggregated weather observations per station
Key Variableswspd: Average wind speed (km/h)wdir: Mean wind direction (degrees)tavg: Average air temperature (°C)coco: Condition codeTime Period: 2024
Locations: ~30
Frame: Hourly and Daily
Units: Metric (km/h, degrees, °C)
#Start of Data ::: {.panel-tabset}
| Regional Wind Analysis by Speed and Direction | ||||
| Hourly Averages 2024 | Data: Meteostat | ||||
| latitude | longitude | Wind Statistics | ||
|---|---|---|---|---|
| Speed (km/h) | Direction (°) | |||
| Case Studies | ||||
| Key West, FL | 24.5551 | -81.78 | 68.3 | 91.0 |
| Honolulu, HI | 21.3069 | -157.8583 | 64.1 | 54.0 |
| Oklahoma City, OK | 35.4676 | -97.5164 | 63.3 | 142.0 |
| Anchorage, AK | 61.2181 | -149.9003 | 29.2 | 358.0 |
| Midwest | ||||
| Cleveland, OH | 41.4993 | -81.6944 | 64.5 | 227.0 |
| Chicago, IL | 41.8781 | -87.6298 | 57.0 | 259.0 |
| Detroit, MI | 42.3314 | -83.0458 | 55.9 | 248.0 |
| Des Moines, IA | 41.5868 | -93.625 | 55.5 | 246.0 |
| Milwaukee, WI | 43.0389 | -87.9065 | 54.5 | 297.0 |
| Minneapolis, MN | 44.9778 | -93.265 | 45.4 | 307.0 |
| Kansas City, MO | 39.0997 | -94.5786 | 44.0 | 2.0 |
| Northeast | ||||
| Buffalo, NY | 42.8864 | -78.8784 | 74.1 | 243.0 |
| Boston, MA | 42.3601 | -71.0589 | 61.5 | 278.0 |
| Philadelphia, PA | 39.9526 | -75.1652 | 49.9 | 297.0 |
| Albany, NY | 42.6526 | -73.7562 | 43.3 | 263.0 |
| Portland, ME | 43.6591 | -70.2568 | 41.2 | 313.0 |
| Pittsburgh, PA | 40.4406 | -79.9959 | 40.7 | 299.0 |
| New York, NY | 40.7128 | -74.006 | 38.3 | 300.0 |
| Southeast | ||||
| New Orleans, LA | 29.9511 | -90.0715 | 69.6 | 133.0 |
| Jacksonville, FL | 30.3322 | -81.6557 | 52.3 | 81.0 |
| Miami, FL | 25.7617 | -80.1918 | 47.3 | 81.0 |
| Tampa, FL | 27.9506 | -82.4572 | 41.8 | 49.0 |
| Charlotte, NC | 35.2271 | -80.8431 | 36.5 | 319.0 |
| Raleigh, NC | 35.7796 | -78.6382 | 34.0 | 345.0 |
| Atlanta, GA | 33.749 | -84.388 | 28.6 | 357.0 |
| West | ||||
| Denver, CO | 39.7392 | -104.9903 | 48.6 | 180.0 |
| San Francisco, CA | 37.7749 | -122.4194 | 48.2 | 294.0 |
| Salt Lake City, UT | 40.7608 | -111.891 | 47.0 | 154.0 |
| Las Vegas, NV | 36.1699 | -115.1398 | 45.2 | 319.0 |
| Los Angeles, CA | 34.0522 | -118.2437 | 39.6 | 208.0 |
| Portland, OR | 45.5152 | -122.6784 | 39.2 | 333.0 |
| Phoenix, AZ | 33.4484 | -112.074 | 37.7 | 128.0 |
| Seattle, WA | 47.6062 | -122.3321 | 30.0 | 191.0 |
| Legend: 🔵North 🔴East 🟡South 🟢West | Darker = Stronger | ||||
click points on the map to see the 2024 wind speeds for a given city. (Shift + click to select multiple cities to compare).
click points on the map to see the wind speeds for the week surrounding a tornado (Shift+ click to select multiple tornados to compare)
How do wind patterns change by region?
What are some case studies of extreme weather?
How do geographical features (lakes, oceans, mountains, deserts, plains) impact wind patterns?